Job Description: Principal Edge Computer Software Engineer – AI Model Integration

Role Summary

The Principal Edge Computer Software Engineer is responsible for leading the end-to-end software lifecycle for AI-enabled edge computing systems deployed on resource-constrained platforms at AI.DA, Strategic Technology Centre (STC)'s Next-gen Edge AI & Robotics Lab (NEAR).

The role focuses on rapid prototyping and deployment of cutting-edge technologies, the Software Engineer is expected to apply the V-cycle in a pragmatic manner. The Software Engineer must tailor or compress processes where appropriate to accelerate delivery and approve waivers or exemptions while ensuring safety, quality, and engineering rigor are maintained. Appropriate level of process rigor to balance speed of execution with operational safety and technical robustness.

Key Responsibilities

• Lead Edge computer software V-cycle for rapid prototypes Proof of Concepts.
• Define software requirements from system functional requirements. Translate requirements into software architecture, class modules and functional components.
• Receive AI model, review and understand the AI model software architecture, including data flow, interfaces, and runtime assumptions.
• Identify integration risks related to CPU/ GPU utilization, memory, latency, and platform limitations, and determine mitigation strategies.
• Adapt middleware-layer software libraries to support AI model execution on edge computers. Insert supplementary code needed to execute AI models, implement source code primarily with auto code generation supplemented with manual coding.
• Integrate hardware abstraction layers, operating system interfaces, device drivers for sensors, GPU accelerators, CUDA, storage, and communication interfaces.
• Ensure efficient resource utilization, robustness, and predictable runtime behavior. Drive performance optimization across CPU / GPU, memory, latency, and power.
• Define and execute comprehensive verification and validation activities, ensuring reliable operation under nominal and degraded conditions.
• Support System in the loop test and Field trials. Receive feedback on software performance, implement improvements, and release improvements through quick CI/CD cycles.
• Release clear documentation stack to release software to business units.

Skill Sets

Programming Languages

- Python:
  - AI model integration and inference scripting
  - Data preprocessing and postprocessing pipelines
  - Automation, tooling, and test harness development

- C++:
  - High-performance and real-time software development
  - Middleware, platform services, and driver-level implementation
  - Integration with hardware accelerators and operating system services

Additional Software Skills

- Embedded Linux development and debugging
- Software architecture and interface design
- Multithreading, concurrency, and memory management
- Build systems and toolchains (e.g., CMake, cross-compilation)
- Software integration and system debugging on resource-constrained platforms
- Performance profiling and optimization
- Familiarity with AI inference frameworks and runtimes is an advantage

Preferred Attributes

- Strong systems engineering mindset and attention to software quality.
- Ability to bridge AI model development teams and embedded software teams.
- Comfortable working across application, middleware, and low-level software layers.
- Effective technical communication and documentation skills.